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Annual Simulation Symposium (ANSS)

The Bubble Bit Technique as Improvement of HDL-Based Quantum Circuits Simulation

Mihai Udrescu, Lucian Prodan, Mircea Vlăduţiu

Published Apr 19, 2005• 12 citations
Publisher

Abstract

When performed on a classical computer, the simulation of quantum circuits is usually an exponential job. The methodology based on Hardware Description Languages is able to isolate the entanglement as source of simulation complexity. However, it was shown that this methodology is not efficient in the presence of total entanglement, and the probability of such a situation grows exponentially with the number of qubits [ M. Udrescu, L. Prodan, M Vladutiu (2004) ]. The bubble bit technique is designed to avoid the entangled representation of the quantum state, thus allowing the HDL structural description of the quantum circuit, which requires polynomial resources for simulation. We provide experimental runtimes, obtained by simulation of quantum arithmetic and Grover's algorithm circuits, which indicate substantial runtime speedup.

DOI
10.1109/anss.2005.43

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When performed on a classical computer, the simulation of quantum circuits is usually an exponential job. The methodology based on Hardware Description Languages is able to isolate the entanglement as source of simulation complexity. However, it was shown that this methodology is not efficient in the presence of total entanglement, and the probability of such a situation grows exponentially with the number of qubits [ M. Udrescu, L. Prodan, M Vladutiu (2004) ]. The bubble bit technique is designed to avoid the entangled representation of the quantum state, thus allowing the HDL structural description of the quantum circuit, which requires polynomial resources for simulation. We provide experimental runtimes, obtained by simulation of quantum arithmetic and Grover's algorithm circuits, which indicate substantial runtime speedup.
The quantum algorithms could efficiently solve problems having exponential classical solutions [8]. The circuit model is considered as the most feasible implementation of the quantum algorithms [17]. This paper tries to find common ground between classical circuit design techniques and quantum computation, by identifying quantum circuit specification and simulation tools under the form of Hardware Description Languages (HDLs). The HDL-based simulation approach could reduce the complexity of quantum circuit simulation, by considering entanglement as the main source of gate-level simulation complexity, and isolating it in an automated manner. This is possible by taking advantage of the HDL feature of describing a circuit with both structural and functional architectures. We also performed an analysis of our methodology effectiveness, for the arithmetic circuits involved in Shor's algorithm and the circuits implementing Grover's algorithm. Our method is further improved by an entangled representation avoidance technique called 'bubble logic insertion'.
It can be shown that if quantum algorithms run on quantum computers, their processing speeds improve exponentially compared to their classical counterparts. However, due to the lack of quantum computers circuit model of quantum algorithms are currently simulated using classical computers to verify their functionalities. On the other hand, software simulation cannot use the intrinsic parallelism of quantum algorithm efficiently. To address the problem, in this paper hardware emulation of quantum algorithms are discussed. To emulate quantum algorithms using FPGAs, a new representation for quantum bits is emulated that improves the emulation of quantum circuits considerably. This representation could be used in both distinct and entangle qubit states.
Simulating quantum computation on a classical computer is a difficult problem. The matrices representing quantum gates, and vectors modeling qubit states grow exponentially with the number of qubits. It has been shown experimentally that the QuIDD (Quantum Information Decision Diagram) datastructure greatly facilitates simulations using memory and runtime that are polynomial in the number of qubits. In this paper, we present a complexity analysis which formally describes this class of matrices and vectors. We also present an improved implementation of QuIDDs which can simulate Grover's algorithm for quantum search with the asymptotic runtime complexity of an ideal quantum computer up to negligible overhead.
Simulating quantum computation on a classical computer is a difficult problem. The matrices representing quantum gates, and vectors modeling qubit states grow exponentially with an increase in the number of qubits. However, by using a new data structure called the Quantum Information Decision Diagram (QuIDD) that exploits the structure of quantum operators, many of these matrices and vectors can be represented in a form that grows polynomially. Using QuIDDs, we implemented a general-purpose quantum computing simulator in C++ called QuIDDPro and tested it on Grover's algorithm. Our QuIDD technique asymptotically outperforms other known simulation techniques.
Simulating quantum computation on a classical com-puter is a difficult problem. The matrices representing quantum gates, and vectors modeling qubit states grow ex-ponentially with the number of qubits. It has been shown ex-perimentally that the QuIDD (Quantum Information Deci-sion Diagram) datastructure greatly facilitates simulations using memory and runtime that are polynomial in the num-ber of qubits. In this paper, we present a complexity analysis which formally describes this class of matrices and vectors. We also present an improved implementation of QuIDDs which can simulate Grover’s algorithm for quantum search with the asymptotic runtime complexity of an ideal quantum computer up to negligible overhead. 1.
An ultimate goal of quantum computing is to perform calculations beyond the reach of any classical computer.It is therefore imperative that useful quantum computers be very difficult to simulate classically, otherwise classical computers could be used for the applications envisioned for the quantum ones.Perfect quantum computers are unarguably exponentially difficult to simulate: the classical resources required grow exponentially with the number of qubits N or the depth D of the circuit.This difficulty has triggered recent experiments on deep, random circuits that aim to demonstrate that quantum devices may already perform tasks beyond the reach of classical computing.These real quantum computing devices, however, suffer from many sources of decoherence and imprecision which limit the degree of entanglement that can actually be reached to a fraction of its theoretical maximum.They are characterized by an exponentially decaying fidelity F ∼ ð1 -ϵÞ ND with an error rate ϵ per operation as small as ≈1% for current devices with several dozen qubits or even smaller for smaller devices.In this work, we provide new insight on the computing capabilities of real quantum computers by demonstrating that they can be simulated at a tiny fraction of the cost that would be needed for a perfect quantum computer.Our algorithms compress the representations of quantum wave functions using matrix product states, which are able to capture states with low to moderate entanglement very accurately.This compression introduces a finite error rate ϵ so that the algorithms closely mimic the behavior of real quantum computing devices.The computing time of our algorithm increases only linearly with N and D in sharp contrast with exact simulation algorithms.We illustrate our algorithms with simulations of random circuits for qubits connected in both one-and twodimensional lattices.We find that ϵ can be decreased at a polynomial cost in computing power down to a minimum error ϵ ∞ .Getting below ϵ ∞ requires computing resources that increase exponentially with ϵ ∞ =ϵ.For a two-dimensional array of N ¼ 54 qubits and a circuit with control-Z gates, error rates better than state-of-the-art devices can be obtained on a laptop in a few hours.For more complex gates such as a SWAP gate followed by a controlled rotation, the error rate increases by a factor 3 for similar computing time.Our results suggest that, despite the high fidelity reached by quantum devices, only a tiny fraction ð∼10 -8 Þ of the system Hilbert space is actually being exploited.